Shankar Narasimhan S

Dynamic simulation models can be used along with flow and pressure measurements, for on-line leak detection and identification in gas pipeline networks. In this two part paper, a methodology is proposed for detecting and localizing leaks occurring in gas pipelines. The main features of the proposed methodology are: (i) it is applicable to both single pipelines and pipeline networks and (ii) it considers non-ideal gas mixtures. In order to achieve the desired computational efficiency for on-line deployment, an efficient state estimation technique based on a transfer function model, previously developed by the authors, is embedded in a hypothesis testing framework. In Part-I of this paper, a detailed description of the methodology is presented, and its performance is evaluated using simulations on two illustrative pipeline systems. The proposed method is shown to perform satisfactorily even with noisy measurements and during transient conditions, provided there is sufficient redundancy in the measurements. © 2010 Elsevier Ltd.

Leakage in water distribution systems is a growing concern throughout the world. Huge amounts of water and energy is wasted through undetected leaks and unauthorized usage in water distribution networks alongside potential health hazards caused by the leaky pipes. As most of the pipelines are buried underground, detecting a leak becomes a complex task. This work focuses on application of graph partitioning technique to Intermittent Water Distribution Networks for identification of leaks without use of a hydraulic model. The network structure is exploited to find the minimum number of valves to be closed or pipes to be isolated, and volume balance is carried out at each stage of partitioning to isolate the leak to a desired level of network resolution. This methodology is applied to a custom built, unique laboratory experimental setup that reflects intermittent water distribution network. The results demonstrate that the leaks can be localized to a smaller part of large network with the application of repeated graph partitioning technique.

Dynamic simulation models of gas pipeline networks can be used for on-line applications such as state estimation, leak detection, etc. A prime requirement for such models is computational efficiency. In this paper, a transfer function model of a gas pipeline is used as a basis for developing a dynamic simulator for gas pipeline networks. The simulator is incorporated in a data reconciliation framework, which is ideally suited for on-line state estimation based on all available measurements of pressures and flow rates. The American Gas Association (AGA) model is used for making realistic computations of the gas compressibility. Accuracy and computational efficiency of the proposed method are evaluated by comparing our results with those obtained using a fully nonlinear second-order accurate finite difference method. The ability of the proposed approach for obtaining accurate state estimation from noisy measurements is demonstrated through simulations on an example network. We also demonstrate the use of the proposed approach for estimating an unknown demand at any node by exploiting the redundancy in measurements. © 2006 American Chemical Society.

Optimal operation of water distribution networks (WDNs) is concerned with meeting consumer demands at desired pressures in an efficient and equitable manner while conserving resources. This can be achieved by implementing advanced control schemes such as model predictive control (MPC). If sufficient water is available, the control objective is to meet consumer demands while preventing wastage. On the other hand, if the available water is insufficient or inadequate to meet consumer demands at the required pressures, equitable distribution of the available resource is of primary importance. In this contribution, a nonlinear model predictive controller is proposed for optimal operation of WDNs that can deal with both the above situations. The proposed approach takes into account availability of storage facilities at the source and demand points. In addition, the control algorithm can account for plant-model mismatch. Performance of the proposed model based control strategy is illustrated through numerical simulations of an illustrative WDN operating under various water availability scenarios. In the water sufficient scenario, the proposed MPC strategy is able to meet the consumer requirements while minimizing the excess amount of water supplied. In the water deficient scenario, the MPC algorithm is able to exploit the available storage facilities at consumer end to reduce the daily supply deficit by about 20%. Using a longer prediction horizon in MPC results in a further reduction of about 40% in the daily supply deficit.

An algorithm is presented for computing the water surface profiles in steady-state gradually varied flows in tree-type open-channel networks. The algorithm is based on the principles of (1) decomposing the channel network into units that are as small as possible; (2) solving the smaller units using an appropriate method, such as the fourth-order Runge-Kutta method; and (3) connecting the solutions for the smaller units to obtain the final solution for the whole network using the Shooting Method. Elementary graph theoretical concepts are utilized to choose the iterative flow variables so that the small units can be solved efficiently. The algorithm is computationally more efficient than the direct method using the Newton-Raphson technique by an order of magnitude. It does not involve the solution of large matrix equations. The efficiency of the algorithm is illustrated by solving an example tree-type channel network with 42 nodes, 41 channels, and a total of 429 grid points. The proposed method will also be very useful in the design and optimization of tree-type channel networks.

In Part-I of this two part paper, a method is proposed for on-line leak detection and identification in gas pipeline networks using flow and pressure measurements. Simulations on two illustrative networks were used to demonstrate the applicability of the proposed method. In this paper, the performance of the proposed leak detection and identification methodology was evaluated using experiments with compressed air on a laboratory scale network. The on-line applicability of the proposed methodology was demonstrated through field level leak detection tests carried out on a 204.7. km long pipeline in India, supplying natural gas to a power plant. The laboratory and field tests demonstrated that the proposed methodology can be used for quick on-line detection of leaks, and locating the leaks reasonably accurately. © 2010 Elsevier Ltd.

In this study, a nonlinear programming approach using the successive quadratic programming optimization technique is developed for the optimal design of a pipeline network for water supply systems. The proposed method eliminates the equality constraints describing the hydraulics by a suitable choice of dependent and independent variables. The dependent variables are chosen based on graph theoretic decomposition of the network structure. This makes it possible to compute analytically the reduced constraints, objective function gradients, and reduced Hessian in a very efficient manner. This method of decomposition ensures that the nodal and loop balances are exactly satisfied and is robust for any initial starting point, able to handle incorrect initial flow directions. The method gives solutions comparable to the previous optimal solutions for the design of new as well as expansion of existing water distribution networks. ©ASCE.

Water distribution networks (WDN) are vulnerable to either intentional or accidental contamination. In order to protect against such intrusions, effective and efficient online monitoring systems are needed. Due to cost and maintenance reasons, it is not possible to locate sensors at each and every potential intrusion point. In this work, we design minimal sensor networks which satisfy the two important properties of observability (ability to detect an intrusion) and identifiability (ability to identify the point of intrusion). Based on the hydraulic analysis of the network, a bipartite graph is constructed between intrusion points and the corresponding nodes that can potentially be affected by the contaminant. The problem of sensor network design is converted to a minimum set cover problem on the bipartite graph, and is solved using a greedy heuristic algorithm. The proposed method is illustrated using a medium scale urban WDN.

Estimation of pipe roughness coefficients is an important task to be carried out before any water distribution network model is used for online applications such as monitoring and control. In this study, a combined state and parameter estimation model for water distribution networks is presented. Typically, estimation of roughness coefficient for each individual pipe is not possible due to non-availability of sufficient number of measurements. In order to address this problem, a formal procedure based on K-means clustering algorithm is proposed for grouping the pipes which are likely to have the same roughness characteristics. Also, graph-theoretic concepts are used to reduce the dimensionality of the problem and thereby achieve significant computational efficiency. The performance of the proposed model is demonstrated on a realistic urban water distribution network. © 2009 Springer Science+Business Media B.V.